CN112465966A - Cliff three-dimensional modeling method integrating oblique photogrammetry and three-dimensional laser scanning - Google Patents

Cliff three-dimensional modeling method integrating oblique photogrammetry and three-dimensional laser scanning Download PDF

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CN112465966A
CN112465966A CN202011311379.XA CN202011311379A CN112465966A CN 112465966 A CN112465966 A CN 112465966A CN 202011311379 A CN202011311379 A CN 202011311379A CN 112465966 A CN112465966 A CN 112465966A
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杨明龙
夏永华
唐秀娟
吕杰
常河
宗慧琳
侯云花
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Kunming University of Science and Technology
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Abstract

The invention discloses a three-dimensional modeling method for a cliff, which integrates oblique photogrammetry and three-dimensional laser scanning; the three-dimensional laser scanning technology is fused with point cloud data acquired by unmanned aerial vehicle low-altitude oblique photogrammetry, and the method can be applied to the fields of archaeology, ancient building modeling, deformation monitoring and the like; the method of combining the ground and the air is adopted for collection, and the defects of measurement model drawing, bottom effect, scanning blind areas shielded from each other in the front and back direction and the like can be mutually compensated by the ground and the air.

Description

Cliff three-dimensional modeling method integrating oblique photogrammetry and three-dimensional laser scanning
Technical Field
The invention belongs to the technical field of geological measurement, and particularly relates to a three-dimensional cliff modeling method integrating oblique photogrammetry and three-dimensional laser scanning.
Background
Due to the self shape, a plurality of data source acquisition blind points exist in the process of establishing a three-dimensional model of a special geographic structure, such as occlusion, angle and position limitation, and if a single device is adopted to acquire a single data source, complete three-dimensional point cloud data is difficult to acquire; the geological landform three-dimensional model established only through a single data source has certain limitations on quality and precision; therefore, the three-dimensional modeling by using multiple devices, multiple platforms and multi-angle data source acquisition and fusion is an effective way for solving the problems and is also a current research hotspot; the multi-platform data acquisition can exert respective advantages, different acquisition modes can adapt to different structural data acquisition, and finally fusion processing is carried out through the data sources acquired in multiple modes, so that the limitation of acquiring the data sources in a single mode can be broken;
the three-dimensional laser scanning technology is fused with point cloud data acquired by unmanned aerial vehicle low-altitude oblique photogrammetry, and the method can be applied to the fields of archaeology, ancient building modeling, deformation monitoring and the like; the method of combining the ground and the air is adopted for collection, and the defects of measurement model drawing, bottom effect, scanning blind areas shielded from each other in the front and back direction and the like can be mutually compensated by the ground and the air.
Disclosure of Invention
The invention aims to solve the problems that the acquisition of a single data source by single equipment is difficult to obtain complete three-dimensional point cloud data, and a three-dimensional model established by the single data source has certain limitations on quality and precision;
in order to solve the technical problems, the invention is realized by the following technical scheme: a cliff three-dimensional modeling method integrating oblique photogrammetry and three-dimensional laser scanning mainly comprises the following four steps: acquiring data of a ground type three-dimensional laser scanning technology, acquiring data of an unmanned aerial vehicle oblique photogrammetry technology, fusing multipoint cloud data and establishing a three-dimensional model;
further, the ground-based three-dimensional laser scanning technology data acquisition comprises the following steps:
(1) performing site survey to determine a main scanning area, and then performing approximate determination of a scanning survey station for the scanning area;
(2) laying a control network, performing control measurement, and obtaining a control point coordinate as a reference for calculating coordinates of the measuring station;
(3) placing a three-dimensional laser scanner, setting parameters of the instrument, and then collecting data;
(4) preprocessing point cloud data by using scanner matching software Maptek I-Site Studio, such as splicing, denoising and the like;
furthermore, in the step (3), the stations are increased or decreased according to the actual situation during data acquisition, generally, on the premise of ensuring the precision, a few viewpoints are used for covering the measurement area, and a sketch is drawn during scanning to facilitate the internal data processing;
furthermore, when the measuring stations are added, the position information of the measuring stations can be unknown, but a scanning area has a certain overlapping degree which is generally not less than 30%; the target can also be used, the target is placed in the scanning area, adjacent stations have at least 3 public targets which are not on the same straight line, and if 4 targets are arranged, the targets are not on the same plane; measuring the accurate coordinates of the target so as to provide a registration reference for the scanning data of different stations;
further, the unmanned aerial vehicle oblique photogrammetry technology data acquisition comprises the following steps:
(1) before data acquisition, control and image control point layout are carried out on a measuring area;
(2) carrying out route planning and adjustment setting of corresponding parameters on the survey area; course overlap 80%, side overlap 80%, flight path high distance departure point height 150 meters;
(3) controlling a 4Pro UAV (unmanned aerial vehicle) for acquiring data;
(4) during data processing, the fuzzy photos are removed, and CntextCapture Center software is adopted for processing to generate point cloud data;
further, the multi-point cloud data fusion adopts a method of combining a unified coordinate system method and an improved ICP algorithm, and the specific steps are as follows:
p is respectively used for three-dimensional laser point cloud and unmanned aerial vehicle oblique photogrammetry image conversion point cloudT,PSIndicating, deleting PSIn the method, redundant data which does not need to be fused are processed by a unified coordinate method at PT,PSAnd searching for the same-name point pair for rough fusion. The data volume of multi-point cloud is large, and P is added for improving the fusion efficiencyT,PSIs uniformly sampled to obtain
Figure BDA0002789918690000021
And finding out local features in the multipoint cloud fusion interface part, and performing rapid fusion on the local features by using an improved ICP algorithm.
And (3) adding a human rotation angle constraint and a dynamic generation coefficient to improve the ICP algorithm:
(1) given the initial q of rigid body transformation0=[R0,t0]T,R0Is an initial rotation matrix, t0As an initial translation vector, let
Figure BDA0002789918690000036
The iteration number k is 0, and the dynamic iteration coefficient h is 0;
(2) estimating a rotation angle θx,θy,θzIs a boundary of, i.e. thetax∈[θxb-Δθxxb+Δθx],θy∈[θyb-Δθyyb+Δθy],θz∈[θzb-Δθzzb+Δθz],θxb,θyb,θzbIs the mean of the rotation angles;
(3) establishing point cloud by ICP algorithm
Figure BDA0002789918690000037
And
Figure BDA0002789918690000038
correlation of (c)k(i);
(4) Calculation of rotation matrix R by singular value decompositionk+1And a translation vector tk+1Q is thenk+1=[Rk+1,tk+1]T
(5) Calculating qk+1Of two adjacent iterations Δ qk+1
(6) Calculated using equation 4
Figure BDA0002789918690000031
I.e. new rigid body transformations (R)k+1,tk+1);
Figure BDA0002789918690000032
(7) Determining the root mean square error RMS, if RSMk+1-RSMkIf > epsilon, then h-h +1 operation is performed, otherwise h-0 operation is performed, and RMS is defined as
Figure BDA0002789918690000033
(8) Judging the dynamic generation coefficient h, if h is greater than 0, executing
Figure BDA0002789918690000034
Updating point set h times
Figure BDA0002789918690000035
(9) Determining the termination condition, if the termination condition satisfies the | RMSk+1-RMSk< ε | or k > StepmaxThe algorithm terminates, otherwise moves to Step (10), ε is a preset threshold, StepmaxIs the maximum number of generations;
(10) let k be k +1 and go to step (2).
Further, the three-dimensional model is established in a mode of reconstructing fused multipoint clouds according to a Delaunay space triangulation algorithm or in a mode of respectively reconstructing unmanned aerial vehicle oblique photogrammetry image conversion point clouds and three-dimensional laser scanning point clouds, and then models obtained in the two modes are fused into a complete three-dimensional model;
further, the fused multipoint cloud is reconstructed according to a Delaunay space triangulation algorithm, and before multipoint cloud data fusion, the point cloud data of the unmanned aerial vehicle oblique photogrammetry image conversion is removed or the data with unsatisfactory quality is removed, and the three-dimensional laser point cloud data is filtered in a unified sampling mode; in the data fusion process, data fusion is not needed to be carried out on all the areas, and only the part with data missing is fused.
The invention has the beneficial effects that: the oblique photogrammetry technology is combined with the ground three-dimensional laser scanning technology to be applied to the high cliff, and the unmanned aerial vehicle oblique photogrammetry image conversion point cloud data and the ground laser scanning point cloud data are subjected to registration and fusion, so that ground three-dimensional laser scanning dead angles are supplemented, and the integrity of the point cloud data of the high cliff is ensured. Because three-dimensional laser penetrability is good, data accuracy is high, can be applied to unmanned aerial vehicle oblique photogrammetry's measured data correction or repair the three-dimensional model with three-dimensional laser scanning technique, solve the not good and local flower problem of data quality. The three-dimensional model built by fusing data has good integrity, strong authenticity, scalability and undistorted proportion, and can obtain better visualization effect and engineering practicability.
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Fig. 1 is a block diagram of the steps of a three-dimensional modeling method for a cliff integrating oblique photogrammetry and three-dimensional laser scanning.
Detailed Description
The present invention will be further described with reference to the following specific examples, but the scope of the present invention is not limited to the contents of the examples;
example 1
The embodiment is based on a Yunnan marble customs scenic spot, is positioned in the Xipo Yangbi county of the cangshan, is a geological park of the cangshan, is located at the west foot of the Longshan Longquan peak and Yujufeng and is located at the east bank of Yangjiang; the scarp is V-shaped, the inclination angle of two walls is about 90 degrees, the scarp is about 450 meters high and is more than one thousand meters long, two quay walls of the canyon are broken by a thousand of the scarp, and a huge stone is abrupt;
1. the method comprises the following steps of performing data acquisition of a ground type three-dimensional laser scanning technology:
(1) performing site survey to determine a main scanning area, and then performing approximate determination of a scanning survey station for the scanning area;
(2) laying a control network, performing control measurement, and obtaining a control point coordinate as a reference for calculating coordinates of the measuring station;
(3) placing a three-dimensional laser scanner, setting parameters of the instrument, and then collecting data; the measurement stations are increased or decreased according to actual conditions during data acquisition, a measurement area is covered by fewer viewpoints on the premise of ensuring the precision, and a sketch is drawn during scanning so as to facilitate the processing of internal data;
(4) preprocessing point cloud data by using scanner matching software Maptek I-Site Studio, such as splicing, denoising and the like;
according to the actual situation of a field, the position information of the measuring station can be unknown when the measuring station needs to be added, but a scanning area has a certain overlapping degree which is generally not less than 30%; the target can also be used, the target is placed in the scanning area, adjacent stations have at least 3 public targets which are not on the same straight line, and if 4 targets are arranged, the targets are not on the same plane; and measuring the accurate coordinates of the target so as to provide a registration reference for the scanning data of different stations.
2. The method comprises the following steps of carrying out data acquisition of the unmanned aerial vehicle oblique photogrammetry technology:
(1) before data acquisition, control and image control point layout are carried out on a measuring area;
(2) carrying out route planning and adjustment setting of corresponding parameters on the survey area; course overlap 80%, side overlap 80%, flight path high distance departure point height 150 meters;
(3) controlling a 4Pro UAV (unmanned aerial vehicle) for acquiring data;
(4) during data processing, the fuzzy photos are removed, and CntextCapture Center software is adopted for processing to generate point cloud data;
3. the method for fusing multi-point cloud data by combining a unified coordinate system method and an improved ICP algorithm comprises the following specific steps:
p is respectively used for three-dimensional laser point cloud and unmanned aerial vehicle oblique photogrammetry image conversion point cloudT,PSIndicating, deleting PSIn the method, redundant data which does not need to be fused are processed by a unified coordinate method at PT,PSAnd searching for the same-name point pair for rough fusion. The data volume of multi-point cloud is large, and P is added for improving the fusion efficiencyT,PSIs uniformly sampled to obtain
Figure BDA0002789918690000051
And finding out local features in the multipoint cloud fusion interface part, and performing rapid fusion on the local features by using an improved ICP algorithm.
And (3) adding a human rotation angle constraint and a dynamic generation coefficient to improve the ICP algorithm:
(8) given the initial q of rigid body transformation0=[R0,t0]T,R0Is an initial rotation matrix, t0As an initial translation vector, let
Figure BDA0002789918690000054
The iteration number k is 0, and the dynamic iteration coefficient h is 0;
(9) estimating a rotation angle θx,θy,θzIs a boundary of, i.e. thetax∈[θxb-Δθxxb+Δθx],θy∈[θyb-Δθyyb+Δθy],θz∈[θzb-Δθzzb+Δθz],θxb,θyb,θzbIs the mean of the rotation angles;
(10) establishing point cloud by ICP algorithm
Figure BDA0002789918690000052
And
Figure BDA0002789918690000053
correlation of (c)k(i);
(11) Calculation of rotation matrix R by singular value decompositionk+1And a translation vector tk+1Q is thenk+1=[Rk+1,tk+1]T
(12) Calculating qk+1Of two adjacent iterations Δ qk+1
(13) Calculated using equation 4
Figure BDA0002789918690000061
I.e. new rigid body transformations (R)k+1,tk+1);
Figure BDA0002789918690000062
(14) Determining the root mean square error RMS, if RSMk+1-RSMkIf > epsilon, then h-h +1 operation is performed, otherwise h-0 operation is performed, and RMS is defined as
Figure BDA0002789918690000063
(8) Judging the dynamic generation coefficient h, if h is greater than 0, executing
Figure BDA0002789918690000064
Updating point set h times
Figure BDA0002789918690000065
(9) Determining the termination condition, if the termination condition satisfies the | RMSk+1-RMSk< ε | or k > StepmaxThe algorithm terminates, otherwise moves to Step (10), ε is a preset threshold, StepmaxIs the maximum number of generations;
(10) let k be k +1 and go to step (2).
4. Establishing a three-dimensional modeling mode by adopting a mode of reconstructing fused multipoint cloud according to a Delaunay space triangulation algorithm or a mode of respectively reconstructing a three-dimensional model by unmanned aerial vehicle oblique photogrammetry image conversion point cloud and a three-dimensional laser scanning point cloud, and then fusing the models obtained in the two modes into a complete three-dimensional model; two modes can be selected from one mode to perform three-dimensional modeling;
the fused multipoint cloud is reconstructed in a Delaunay space triangulation algorithm mode, and before multipoint cloud data fusion, point cloud decoration or data with unsatisfactory quality of unmanned aerial vehicle oblique photogrammetry image conversion are respectively eliminated, and three-dimensional laser point cloud data are filtered in a unified sampling mode; in the data fusion process, data fusion is not needed to be carried out on all the areas, and only the part with data missing is fused.
In summary, the oblique photogrammetry technology is combined with the ground three-dimensional laser scanning technology to be applied to the high cliff, and the unmanned aerial vehicle oblique photogrammetry image conversion point cloud data and the ground laser scanning point cloud data are registered and fused, so that the ground three-dimensional laser scanning dead angle is supplemented, and the integrity of the point cloud data of the high cliff is ensured. Because three-dimensional laser penetrability is good, data accuracy is high, can be applied to unmanned aerial vehicle oblique photogrammetry's measured data correction or repair the three-dimensional model with three-dimensional laser scanning technique, solve the not good and local flower problem of data quality. The three-dimensional model built by fusing data has good integrity, strong authenticity, scalability and undistorted proportion, and can obtain better visualization effect and engineering practicability.

Claims (8)

1. A cliff three-dimensional modeling method integrating oblique photogrammetry and three-dimensional laser scanning mainly comprises the following three steps: the method comprises the steps of ground type three-dimensional laser scanning technology data acquisition, unmanned aerial vehicle oblique photogrammetry technology data acquisition, multipoint cloud data fusion and three-dimensional model establishment.
2. The cliff three-dimensional modeling method integrating oblique photogrammetry and three-dimensional laser scanning as recited in claim 1, wherein the ground-based three-dimensional laser scanning technology data acquisition comprises the following steps:
(1) performing site survey to determine a main scanning area, and then performing approximate determination of a scanning survey station for the scanning area;
(2) laying a control network, performing control measurement, and obtaining a control point coordinate as a reference for calculating coordinates of the measuring station;
(3) placing a three-dimensional laser scanner, setting parameters of the instrument, and then collecting data;
(4) and (3) carrying out preprocessing such as splicing, denoising and the like on the point cloud data by using scanner matching software Maptek I-Site Studio.
3. The three-dimensional modeling method for the cliff integrating oblique photogrammetry and three-dimensional laser scanning as claimed in claim 2, wherein in the step (3), stations are increased or decreased according to actual conditions during data acquisition, generally, on the premise of ensuring accuracy, a measuring area is covered by fewer viewpoints, and a sketch is drawn during scanning to facilitate internal data processing.
4. The three-dimensional modeling method for the cliff integrating oblique photogrammetry and three-dimensional laser scanning as claimed in claim 3, wherein the stations are increased or decreased according to actual conditions during data acquisition, and when the stations are increased, the position information of the stations can be unknown, but the scanning area has a certain overlapping degree, generally not less than 30%; the target can also be used, the target is placed in the scanning area, adjacent stations have at least 3 public targets which are not on the same straight line, and if 4 targets are arranged, the targets are not on the same plane; and measuring the accurate coordinates of the target so as to provide a registration reference for the scanning data of different stations.
5. The three-dimensional cliff modeling method integrating oblique photogrammetry and three-dimensional laser scanning as recited in claim 1, wherein the unmanned aerial vehicle oblique photogrammetry technology data acquisition comprises the following steps:
(1) before data acquisition, control and image control point layout are carried out on a measuring area;
(2) carrying out route planning and adjustment setting of corresponding parameters on the survey area; course overlap 80%, side overlap 80%, flight path high distance departure point height 150 meters;
(3) controlling a 4Pro UAV (unmanned aerial vehicle) for acquiring data;
(4) and during data processing, the fuzzy photos are removed, and CntextCapture Center software is adopted for processing to generate point cloud data.
6. The cliff three-dimensional modeling method integrating oblique photogrammetry and three-dimensional laser scanning as claimed in claim 1, wherein the multi-point cloud data fusion adopts a method combining a unified coordinate system method and an improved ICP algorithm, and comprises the following specific steps:
p is respectively used for three-dimensional laser point cloud and unmanned aerial vehicle oblique photogrammetry image conversion point cloudT,PSIndicating, deleting PSIn the method, redundant data which does not need to be fused are processed by a unified coordinate method at PT,PSAnd searching for the same-name point pair for rough fusion. The data volume of multi-point cloud is large, and P is added for improving the fusion efficiencyT,PSIs uniformly sampled to obtain
Figure FDA0002789918680000025
And finding out local features in the multipoint cloud fusion interface part, and performing rapid fusion on the local features by using an improved ICP algorithm.
And (3) adding a human rotation angle constraint and a dynamic generation coefficient to improve the ICP algorithm:
(1) given the initial q of rigid body transformation0=[R0,t0]T,R0Is an initial rotation matrix, t0As an initial translation vector, let
Figure FDA0002789918680000021
The iteration number k is 0, and the dynamic iteration coefficient h is 0;
(2) estimating a rotation angle θx,θy,θzIs a boundary of, i.e. thetax∈[θxb-Δθxxb+Δθx],
Figure FDA0002789918680000022
θz∈[θzb-Δθzzb+Δθz],θxb,θyb,θzbIs the mean of the rotation angles;
(3) establishing point cloud by ICP algorithm
Figure FDA0002789918680000026
And
Figure FDA0002789918680000027
correlation of (c)k(i);
(4) Calculation of rotation matrix R by singular value decompositionk+1And a translation vector tk+1Q is thenk+1=[Rk+1,tk+1]T
(5) Calculating qk+1Of two adjacent iterations Δ qk+1
(6) Calculated using equation 4
Figure FDA0002789918680000023
I.e. new rigid body transformations (R)k+1,tk+1);
Figure FDA0002789918680000024
(7) Determining the root mean square error RMS, if RSMk+1-RSMkIf > epsilon, then h-h +1 operation is performed, otherwise h-0 operation is performed, and RMS is defined as
Figure FDA0002789918680000031
(8) Judging the dynamic generation coefficient h, if h is greater than 0, executing
Figure FDA0002789918680000032
Updating points h timesCollection
Figure FDA0002789918680000033
(9) Determining the termination condition, if the termination condition satisfies the | RMSk+1-RMSk< ε | or k > StepmaxThe algorithm terminates, otherwise moves to Step (10), ε is a preset threshold, StepmaxIs the maximum number of generations;
(10) let k be k +1 and go to step (2).
7. The three-dimensional cliff modeling method integrating oblique photogrammetry and three-dimensional laser scanning as claimed in claim 1, wherein the three-dimensional model is built in a mode of reconstructing a fused multi-point cloud according to a Delaunay space triangulation algorithm or in a mode of respectively reconstructing a three-dimensional model by using an unmanned aerial vehicle oblique photogrammetry image conversion point cloud and a three-dimensional laser scanning point cloud, and then the models obtained in the two modes are fused into a complete three-dimensional model.
8. The three-dimensional cliff modeling method integrating oblique photogrammetry and three-dimensional laser scanning as claimed in claim 7, wherein the fused multi-point cloud is reconstructed by a Delaunay space triangulation algorithm, and before multi-point cloud data fusion, unmanned aerial vehicle oblique photogrammetry image conversion point cloud decoration or data with poor quality are respectively removed and three-dimensional laser point cloud data are filtered by a uniform sampling method; in the data fusion process, data fusion is not needed to be carried out on all the areas, and only the part with data missing is fused.
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